Examining the effects of birth order on personality


  • 1 Department of Psychology, University of Leipzig, 04109 Leipzig, Germany;
  • 2 Department of Psychology, Johannes Gutenberg University of Mainz, 55099 Mainz, Germany.
  • 3 Department of Psychology, University of Leipzig, 04109 Leipzig, Germany; [email protected].
  • PMID: 26483461
  • PMCID: PMC4655522
  • DOI: 10.1073/pnas.1506451112

This study examined the long-standing question of whether a person's position among siblings has a lasting impact on that person's life course. Empirical research on the relation between birth order and intelligence has convincingly documented that performances on psychometric intelligence tests decline slightly from firstborns to later-borns. By contrast, the search for birth-order effects on personality has not yet resulted in conclusive findings. We used data from three large national panels from the United States (n = 5,240), Great Britain (n = 4,489), and Germany (n = 10,457) to resolve this open research question. This database allowed us to identify even very small effects of birth order on personality with sufficiently high statistical power and to investigate whether effects emerge across different samples. We furthermore used two different analytical strategies by comparing siblings with different birth-order positions (i) within the same family (within-family design) and (ii) between different families (between-family design). In our analyses, we confirmed the expected birth-order effect on intelligence. We also observed a significant decline of a 10th of a SD in self-reported intellect with increasing birth-order position, and this effect persisted after controlling for objectively measured intelligence. Most important, however, we consistently found no birth-order effects on extraversion, emotional stability, agreeableness, conscientiousness, or imagination. On the basis of the high statistical power and the consistent results across samples and analytical designs, we must conclude that birth order does not have a lasting effect on broad personality traits outside of the intellectual domain.

Keywords: Big Five; birth order; personality; siblings; within-family analyses.

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  • Comparative Study
  • Multicenter Study
  • Aged, 80 and over
  • Databases, Factual*
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  • Middle Aged
  • Parturition*
  • Personality*
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The Reporter

New Evidence on the Impacts of Birth Order

What determines a child's success? We know that family matters — children from higher socioeconomic status families do better in school, get more education, and earn more.

However, even beyond that, there is substantial variation in success across children within families. This has led researchers to study factors that relate to within-family differences in children's outcomes. One that has attracted much interest is the role played by birth order, which varies systematically within families and is exogenously determined.

While economists have been interested in understanding human capital development for many decades, compelling economic research on birth order is more recent and has largely resulted from improved availability of data. Early work on birth order was hindered by the stringent data requirements necessary to convincingly identify the effects of birth order. Most importantly, one needs information on both family size and birth order. As there is only a third-born child in a family with at least three children, comparing third-borns to firstborns across families of different sizes will conflate the birth order effect with a family size effect, so one needs to be able to control for family size. Additionally, it is beneficial to have information on multiple children from the same family so that birth order effects can be estimated from within-family differences in child outcomes; otherwise, birth order effects will be conflated with other effects that vary systematically with birth order, such as cohort effects. Large Scandinavian register datasets that became available to researchers beginning in the late 1990s have enabled birth order research, as they contain population data on both family structure and a variety of child outcomes. Here, I describe my research with a number of coauthors, using these data to explore the effects of birth order on outcomes including human capital accumulation, earnings, development of cognitive and non-cognitive skills, and health.

Birth Order and Economic Success

Almost a half-century ago, economists including Gary Becker, H. Gregg Lewis, and Nigel Tomes created models of quality-quantity trade-offs in child-rearing and used these models to explore the role of family in children's success. They sought to explain an observed negative correlation between family income and family size: if child quality is a normal good, as income rises the family demands higher-quality children at the cost of lower family size. 1

However, this was a difficult model to test, as characteristics other than family income and child quality vary with family size. The introduction of natural experiments, combined with newly available large administrative datasets from Scandinavia, made testing such a model possible.

In my earliest work on the topic, Paul Devereux, Kjell Salvanes, and I took advantage of the Norwegian administrative dataset and set out to better understand this theoretical quantity-quality tradeoff. 2 It became clear that child "quality" was not a constant within a family — children within families were quite different, despite the model assumptions to the contrary. Indeed, we found that birth order could explain a large fraction of the family size differential in children's educational outcomes. Average educational attainment was lower in larger families largely because later-born children had lower average education, rather than because firstborns had lower education in large families than in small families. We found that firstborns had higher educational attainment than second-borns who in turn did better than third-borns, and so on. These results were robust to a variety of specifications; most importantly, we could compare outcomes of children within the same families.


To give a sense of the magnitude of these effects: The difference in educational attainment between the first child and the fifth child in a five-child family is roughly equal to the difference between the educational attainment of blacks and whites calculated from the 2000 Census. We augmented the education results by examining earnings, whether full-time employed, and whether one had a child as a teenager as additional outcome variables, and found strong evidence for birth order effects, particularly for women. Later-born women have lower earnings (whether employed full-time or not), are less likely to work full-time, and are more likely to have their first child as teenagers. In contrast, while later-born men have lower full-time earnings, they are not less likely to work full-time [Figure 1].

Birth Order and Cognitive Skills

One possible explanation for these differences is that cognitive ability varies systematically by birth order. In subsequent work, Devereux, Salvanes, and I examined the effect of birth order on IQ scores. 3

The psychology literature has long debated the role of birth order in determining children's IQs; this debate was seemingly resolved when, in 2000, J. L. Rodgers et al. published a paper in American Psychologist entitled "Resolving the Debate Over Birth Order, Family Size, and Intelligence" that referred to the apparent relationship between birth order and IQ as a "methodological illusion." 4 However, this work was limited due to the absence of large representative datasets necessary to identify these effects. We again used population register data from Norway to estimate this relationship.

To measure IQ, we used the outcomes of standardized cognitive tests administered to Norwegian men between the age of 18 and 20 when they enlist in the military. Consistent with our earlier findings on educational attainment but in contrast to the previous work in the literature, we found strong birth order effects on IQ that are present when we look within families. Later-born children have lower IQs, on average, and these differences are quite large. For example, the difference between firstborn and second-born average IQ is on the order of one-fifth of a standard deviation, or about three IQ points. This translates into approximately a 2 percent difference in annual earnings in adulthood.

The Effect of Birth Order on Non-Cognitive Skills

Personality is another factor that is posited to vary by birth order, a proposition that has been particularly difficult to assess in a compelling way due to the paucity of large datasets containing information on individual personality. In recent work on the topic, Erik Gronqvist, Bjorn Ockert, and I use Swedish administrative datasets to examine this issue. 5

In the economics literature, personality traits are often referred to as non-cognitive abilities and denote traits that can be distinguished from intelligence. 6 To measure "personality" (or non-cognitive skills), we use the outcome of a standardized psychological evaluation, conducted by a certified psychologist, that is performed on all Swedish men between the ages of 18 and 20 when they enlist in the military, and which is strongly related to success in the labor market. An individual is given a higher score if he is considered to be emotionally stable, persistent, socially outgoing, willing to assume responsibility, and able to take initiative. Similar to the results for cognitive skills, we find evidence of consistently lower scores in this measure for later-born children. Third-born children have non-cognitive abilities that are 0.2 standard deviations below firstborn children. Interestingly, boys with older brothers suffer almost twice as much in terms of these personality characteristics as boys with older sisters.


Importantly, we also demonstrate that these personality differences translate into differences in occupation choice by birth order. Firstborn children are significantly more likely to be employed and to work as top managers, while later-born children are more likely to be self-employed. More generally, firstborn children are more likely to be in occupations requiring sociability, leadership ability, conscientiousness, agreeableness, emotional stability, extraversion, and openness.

The Effect of Birth Order on Health

Finally, how do these differences translate into later health? In more recent work, Devereux, Salvanes, and I analyze the effect of birth order on health. 7 There is a sizable body of literature about the relationship between birth order and adult health; individual studies have typically examined only one or a small number of health outcomes and, in many cases, have used relatively small samples. Again, we use large nationally representative data from Norway to identify the relationship between birth order and health when individuals are in their 40s, where health is measured along a number of dimensions, including medical indicators, health behaviors, and overall life satisfaction.

The effects of birth order on health are less straightforward than other outcomes we have examined, as firstborns do better on some dimensions and worse on others. We find that the probability of having high blood pressure declines with birth order, and the largest gap is between first- and second-borns. Second-borns are about 3 percent less likely to have high blood pressure than firstborns; fifth-borns are about 7 percent less likely to have high blood pressure than firstborns. Given that 24 percent of this population has high blood pressure, this is quite a large difference. Firstborns are also more likely to be overweight and obese. Compared with second-borns, firstborns are 4 percent more likely to be overweight and 2 percent more likely to be obese. The equivalent differences between fifth-borns and firstborns are 10 percent and 5 percent. For context, 47 percent of the population is overweight and 10 percent is obese. Once again, the magnitudes are quite large.

However, later-borns are less likely to consider themselves to be in good health, and measures of mental health generally decline with birth order. Later-born children also exhibit worse health behaviors. The number of cigarettes smoked daily increases monotonically with birth order, suggesting that the higher prevalence of smoking by later-borns found among U.S. adolescents by Laura M. Argys et al. 8 may persist throughout adulthood and, hence, have important effects on health outcomes.

Possible Mechanisms

Why are adult outcomes likely to be affected by birth order? A host of potential explanations has been proposed across several academic disciplines.

A number of biological factors may explain birth order effects. These relate to changes in the womb environment or maternal immune system that occur over successive births. Beyond biology, parents could have other influences. Childhood inputs, especially in the first years of life, are considered crucial for skill formation. 9 Firstborn children have the full attention of parents, but as families grow the family environment is diluted and parental resources become scarcer. 10 In contrast, parents are more experienced and tend to have higher incomes when raising later-born children. In addition, for a given amount of resources, parents may treat firstborn children differently than second- or later-born children. Parents may use more strict parenting practices toward the firstborn, so as to gain a reputation for "toughness" necessary to induce good behavior among later-borns. 11

There are also theories that suggest that interactions among siblings can shape birth order effects. For example, based on evolutionary psychology, Frank J. Sulloway suggests that firstborns have an advantage in following the status quo, while later-borns — by having incentives to engage in investments aimed at differentiating themselves — become more sociable and unconventional in order to attract parental resources. 12

In each of these papers, we attempted to identify potential mechanisms for the patterns we observed. However, it is here we see the limitations of these large administrative datasets, as for the most part, we lack necessary detailed information on biological factors and on household dynamics when the children are young. However, we do have some evidence on the role of biological factors. Later-born children tend to have better birth outcomes as measured by factors such as birth weight. In our Swedish data, we took advantage of the fact that some children's biological birth order is different from their environmental birth order, due to the death of an older sibling or because their parent gave up a child for adoption. When we examine this subsample, we find that the birth order effect on occupational choice is entirely driven by the environmental birth order, again suggesting that biological factors may not be central.

Also in our Swedish study, we found that firstborn teenagers are more likely to read books, spend more time on homework, and spend less time watching TV or playing video games. Parents spend less time discussing school work with later-born children, suggesting there may be differences in parental time investments. Using Norwegian data, we found that smoking early in pregnancy is more prevalent for first pregnancies than for later ones. However, women are more likely to quit smoking during their first pregnancy than during later ones, and firstborns are more likely to be breastfed. These findings suggest that early investments may systematically benefit firstborns and help explain their generally better outcomes.

In the past two decades, with the increased accessibility of administrative datasets on large swaths of the population, economists and other researchers have been better able to identify the role of birth order in the outcomes of children. There is strong evidence of substantial differences by birth order across a range of outcomes. While I have described several of my own papers on the topic, a number of other researchers have also taken advantage of newly available datasets in Florida and Denmark to examine the role of birth order on other important outcomes, specifically juvenile delinquency and later criminal behavior. 13 Consistent with the work discussed here, later-born children experience higher rates of delinquency and criminal behavior; this is at least partly attributable to time investments of parents.


More from nber.

G. Becker, "An Economic Analysis of Fertility," in Demographic and Economic Change in Developed Countries , New York, Columbia University Press, 1960, pp. 209-40; G. Becker and H. Lewis, "Interaction Between Quantity and Quality of Children," in Economics of the Family: Marriage, Children, and Human Capital , 1974, pp. 81-90; G. Becker and N. Tomes, "Child Endowments, and the Quantity and Quality of Children," NBER Working Paper 123 , February 1976.  

S. Black, P. Devereux, and K. Salvanes, "The More the Merrier? The Effect of Family Composition on Children's Education" NBER Working Paper 10720 , September 2004, and Quarterly Journal of Economics , 120(2), 2005, pp. 669-700.  

S. Black, P. Devereux, and K. Salvanes, "Older and Wiser? Birth Order and the IQ of Young Men," NBER Working Paper 13237 , July 2007, and CESifo Economic Studies , Oxford University Press, vol. 57(1), pages 103-20, March 2011.  

J. Rodgers, H. Cleveland, E. van den Oord, and D. Rowe, "Resolving the Debate Over Birth Order, Family Size, and Intelligence," American Psychologist , 55(6), 2000, pp. 599-612.

S. Black, E. Gronqvist, and B. Ockert, "Born to Lead? The Effect of Birth Order on Non-Cognitive Abilities," NBER Working Paper 23393 , May 2017.  

L. Borghans, A. Duckworth, J. Heckman, and B. ter Weel, "The Economics and Psychology of Personality Traits," Journal of Human Resources , 43, 2008, pp. 972-1059.  

S. Black, P. Devereux, K. Salvanes, "Healthy (?), Wealthy, and Wise: Birth Order and Adult Health, NBER Working Paper 21337 , July 2015.  

L. Argys, D. Rees, S. Averett, and B. Witoonchart, "Birth Order and Risky Adolescent Behavior," Economic Inquiry , 44(2), 2006, pp. 215-33.  

F. Cunha and J. Heckman, "The Technology of Skill Formation," NBER Working Paper 12840 , January 2007.

R. Zajonc and G. Markus, "Birth Order and Intellectual Development," Psychological Review , 82(1), 1975, pp. 74-88; R. Zajonc, "Family Configuration and Intelligence," Science , 192(4236), 1976, pp. 227-36; J. Price, "Parent-Child Quality Time: Does Birth Order Matter?" in Journal of Human Resources , 43(1), 2008, pp. 240-65; J.Lehmann, A. Nuevo-Chiquero, and M. Vidal-Fernandez, "The Early Origins of Birth Order Differences in Children's Outcomes and Parental Behavior," forthcoming in Journal of Human Resources .  

V. Hotz and J. Pantano, "Strategic Parenting, Birth Order, and School Performance," NBER Working Paper 19542 , October 2013, and Journal of Population Economics , 28(4), 2015, pp. 911-936. ↩  

F. Sulloway, Born to Rebel: Birth Order, Family Dynamics, and Creative Lives , New York, Pantheon Books, 1996.

S. Breining, J. Doyle, D. Figlio, K. Karbownik, J. Roth, "Birth Order and Delinquency: Evidence from Denmark and Florida," NBER Working Paper 23038 , January 2017.

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In This Article Expand or collapse the "in this article" section Birth Order

Introduction, general overviews.

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  • Sibling Niche Theory
  • Methodological Issues and Research Design
  • Politics and the Life Sciences Controversy: Agendas and Methodology
  • Birth Order Stereotypes
  • Personality
  • Family Dynamics
  • Friendship and Cooperation
  • Sexual/Romantic Relationships
  • Sexual Orientation and the Fraternal Birth Order Effect
  • Intelligence
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Birth Order by Catherine Salmon LAST REVIEWED: 29 October 2013 LAST MODIFIED: 29 October 2013 DOI: 10.1093/obo/9780199828340-0103

Birth order, defined as an individual’s rank by age among siblings, has long been of interest to psychologists as well as lay-people. Much of the fascination has focused on the possible role of birth order in shaping personality and behavior. Many decades ago, Alfred Adler, a contemporary of Sigmund Freud and Carl Jung, suggested that personality traits are related to a person’s ordinal position within the family. He claimed that firstborns, once the sole focus of parental attention and resources, would be resentful when attention shifted upon the birth of the next child, and that this would result in neuroticism and possible substance abuse. In his view, lastborns would be spoiled and emotionally immature, while middle children would be the most stable, as they never experienced dethronement or being spoiled. Adler’s work led to an explosion of birth order studies examining the relationships between birth order and pretty much any topic one can think of, from personality traits to psychiatric disorders, intelligence, creativity, and sexual orientation. Not all of the research employed controls for other relevant factors, a number of hard-hitting critiques of the field were made, and the number of studies being done waned. Currently, the common view is that genetic differences account for a substantial portion (around 40 percent) of the variance in personality, for example, but that a similar amount of variance (around 35 percent) is due to non-shared environment, while the remainder is due to shared environment and measurement error. Birth order is one part of the non-shared environment. Siblings may grow up in the same family, but they do not all experience that family environment in the same way. Recently, researchers have suggested that birth order shapes strategies for dealing with the family environment, some of which may manifest themselves in settings outside the family domain. The first section of this article introduces general overviews or reviews of the birth order literature as well as some general theoretical perspectives and aspects of the debate over the important of birth order effects. The remaining sections examine the research in various areas where birth order has been well studied.

A wide variety of articles and books provide insight into the theoretical perspectives on birth order as well as reviewing portions of the field. Birth order research touches on many somewhat specialized areas of psychology; for example, cognition, child and lifespan development, social, and personality psychology, and reviews typically focus on just one specific aspect, most frequently personality. Research can be largely atheoretical or may come from an Adlerian perspective or a Darwinian one. There are a number of books and reviews that challenge the impact of birth order, including Harris 1998 , and just as many that argue for strong effects, such as Sulloway 1996 and Sulloway 2010 . Those interested in mastering the birth order literature have a lot of reading ahead of them; thousands of articles have been published. But the articles and books included here will acquaint the reader with the major debates within the field and will highlight the most consistent of findings (and the least). The narrative review of Schooler 1972 provides evidence that the impact of birth order is overstated, while Ernst and Angst 1983 is a well known review of the birth order literature from the 1940s to 1980 that suggests that birth order does not influence personality. Many of the studies it references later became part of Sulloway’s meta-analysis. Plomin, et al. 2001 revisits the role of non-shared environment in answering the question of why siblings are so different from each other with a behavioral genetics influence. Eckstein 2000 and Eckstein, et al. 2010 are influenced by the Adlerian perspective and focus mainly on studies that providence evidence for birth order differences in personality traits.

Eckstein, D. 2000. Empirical studies indicating significant birth-order related personality differences. Journal of Individual Psychology 56:481–494.

A review of studies, largely published between 1960 and 1999, that provides support for birth order differences in personality. Includes studies that relate to traits of firstborns, middleborns, lastborns, and only children. Shows the range of study topics from conformity to narcissism. Illustrates greater research focus on firstborns historically.

Eckstein, D., K. J. Aycock, M. A. Sperber, et al. 2010. A review of 200 birth-order studies: Lifestyle characteristics . Journal of Individual Psychology 66:408–434.

Gives Adlerian perspective and reviews Sulloway and his critics. Provides tables of characteristics by birth order (first/middle/last/only) and the statistically significant related studies from 1960–2010. Does not address non-significant study results, but an otherwise comprehensive reference.

Ernst, C., and J. Angst. 1983. Birth order: Its influence on personality . New York: Springer.

Extensive review of birth order literature from 1946 to 1980. Concludes that effects are the result of poor research design, in particular failure to control for family size and socioeconomic status. Suggests that effects are found more often in studies that fail to control and are not found in ones with proper controls. The meta-analysis of Sulloway 1996 was a statistical counter to this paper.

Harris, J. R. 1998. The nurture assumption: Why children turn out the way they do . New York: Free Press.

Argues that genes and peers shape personality more than parents (and by extension birth order) do and that, while parental love and attention are not distributed evenly and siblings do compete, these experiences do not translate into their relationships with non-kin. Focuses more on peers and socialization.

Plomin, R., K. Asbury, P. G. Dip, and J. Dunn. 2001. Why are children in the same family so different? Non-shared environment a decade later. Canadian Journal of Psychiatry 46:225–233.

Behavioral genetics approach considers what aspects make up non-shared environment for siblings (parental favoritism, peers, interaction between genetics and environment). Plomin is one of first to highlight this question. Calls for more research and for consideration of role of chance. Available online for purchase or by subscription.

Schooler, C. 1972. Birth order effects: Not here, not now. Psychological Bulletin 78:161–175.

DOI: 10.1037/h0033026

Early narrative review of the literature on “normal” and psychiatric populations. Raises family size issues. No discussion of issues involved with using self-report of parental treatment of offspring. Studies are largely confined to comparing firstborns to lastborns or laterborns (everyone but firstborns), which is another issue not discussed (see Methodological Issues and Research Design ). Available online for purchase or by subscription.

Sulloway, F. J. 1996. Born to rebel: Birth order, family dynamics, and creative lives . New York: Pantheon.

Makes solid case for Darwinian theoretical approach to birth order focusing on differential parental investment and sibling competition. Documents personality differences and how they play out in terms of revolutions in science, religion, and politics. Highlights the rebellious role of the laterborn child.

Sulloway, F. J. 2010. Why siblings are like Darwin’s finches: Birth order, sibling competition, and adaptive divergence within the family. In The Evolution of Personality and Individual Differences . Edited by D. M. Buss and P. H. Hawley, 86–119. Oxford: Oxford Univ. Press.

DOI: 10.1093/acprof:oso/9780195372090.001.0001

Darwinian approach to birth order, personality divergence among siblings due to differential parental investment and sibling conflict. Focus on sibling niche picking and that sibling divergence is an adaptive strategy. Covers wide range of studies in review.

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January 1, 2010

How Birth Order Affects Your Personality

For decades the evidence has been inconclusive, but new studies show that family position may truly affect intelligence and personality

By Joshua K. Hartshorne


Sally Anscombe Getty Images

WHEN I TELL PEOPLE I study whether birth order affects personality, I usually get blank looks. It sounds like studying whether the sky is blue. Isn’t it common sense? Popular books invoke birth order for self-discovery, relationship tips, business advice and parenting guidance in titles such as The Birth Order Book: Why You Are the Way You Are (Revell, 2009). Newspapers and morning news shows debate the importance of the latest findings (“Latter-born children engage in more risky behavior; what should parents do?”) while tossing in savory anecdotes (“Did you know that 21 of the first 23 astronauts into space were firstborns?”).

But when scientists scrutinized the data, they found that the evidence just did not hold up. In fact, until very recently there were no convincing findings that linked birth order to personality or behavior. Our common perception that birth order matters was written off as an example of our well-established tendency to remember and accept evidence that supports our pet theories while readily forgetting or overlooking that which does not. But two studies from the past three years finally found measurable effects: our position in the family does indeed affect both our IQ and our personality. It may be time to reconsider birth order as a real influence over whom we grow up to be.

Size Matters Before discussing the new findings, it will help to explain why decades of research that seemed to show birth-order effects was, in fact, flawed. Put simply, birth order is intricately linked to family size. A child from a two-kid family has a 50 percent chance of being a firstborn, whereas a child from a five-kid family has only a 20 percent chance of being a firstborn. So the fact that astronauts are disproportionately firstborns, for example, could merely show that they come from smaller families—not that firstborns have any particularly astronautic qualities. (Of course, firstborns may indeed have astronautic qualities. The point is that with these data, we cannot tell.)

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There are many reasons that family size could affect our predilections and personalities. More children mean that parental resources (money, time and attention) have to be spread more thinly. Perhaps more telling, family size is associated with many important social factors, such as ethnicity, education and wealth. For example, wealthier, better-educated parents typically have fewer children. If astronauts are more likely to have well-educated, comfortable parents, then they are also more likely to come from a smaller family and thus are more likely to be a firstborn.

Of the some 65,000 scholarly articles about birth order indexed by Google Scholar, the vast majority suffer from this problem, making the research difficult to interpret. Many of the few remaining studies fail to show significant effects of birth order. In 1983 psychiatrists Cecile Ernst and Jules Angst of the University of Zurich determined, after a thorough review of the literature, that birth-order effects were not supported by the evidence. In 1998 psychologist Judith Rich Harris published another comprehensive attack on the concept in The Nurture Assumption (Free Press). By 2003 cognitive scientist Steven Pinker of Harvard University found it necessary to spend only two pages of his 439-page discussion of nature and nurture, The Blank Slate (Penguin), dismissing birth order as irrelevant.

New Evidence Even so, the case in 2003 against birth-order effects was mainly an absence of good evidence, rather than evidence of an absence. In fact, the past few years have provided good news for the theory. In 2007 Norwegian epidemiologists Petter Kristensen and Tor Bjerkedal published work showing a small but reliable negative correlation between IQ and birth order: the more older siblings one has, the lower one’s IQ. Whether birth order affects intelligence has been debated inconclusively since the late 1800s, although the sheer size of the study (about 250,000 Norwegian conscripts) and the rigorous controls for family size make this study especially convincing.

In 2009 my colleagues and I published evidence that birth order influences whom we choose as friends and spouses. Firstborns are more likely to associate with firstborns, middle-borns with middle-borns, last-borns with last-borns, and only children with only children. Because we were able to show the effect independent of family size, the finding is unlikely to be an artifact of class or ethnicity. The result is exactly what we should expect if birth order affects personality. Despite the adage that opposites attract, people tend to resemble their spouses in terms of personality. If spouses correlate on personality, and personality correlates with birth order, spouses should correlate on birth order.

Thus, the evidence seems to be shifting back in favor of our common intuition that our position in our family somehow affects who we become. The details, however, remain vague. The Norwegian study shows a slight effect on intelligence. The relationship study shows that oldest, middle, youngest and only children differ in some way yet gives no indication as to how. Moreover, although these effects are reasonably sized by the standards of research, they are small enough that it would not make any sense to organize college admissions or dating pools around birth order, much less NASA applicants.

Still, I expect people—myself included—will continue to try to make sense of the world through the prism of birth order. It’s fine for scientists to say “more study is needed,” but we must find love, gain self-knowledge and parent children now . In that sense, a great deal about who we are and how we think can be learned reading those shelves of birth order–related self-help books, even if the actual content is not yet—or will never be—experimentally confirmed.

Note this story was originally published with the title "Ruled by Birth Order?"

Joshua K. Hartshorne is a Ruth L. Kirschstein NRSA post-doctoral fellow in the Computational Cognitive Science group at MIT and an occasional contributor to Scientific American Mind. He conducts research both in his brick-and-mortar laboratory and online at GamesWithWords.org. You can follow him on Twitter at @jkhartshorne.

SA Mind Vol 20 Issue 7

Birth order and unwanted fertility

  • Original Paper
  • Published: 22 August 2019
  • Volume 33 , pages 413–440, ( 2020 )

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  • Wanchuan Lin 1 ,
  • Juan Pantano 2 &
  • Shuqiao Sun 3  

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An extensive literature documents the effects of birth order on various individual outcomes, with later-born children faring worse than their siblings. However, the potential mechanisms behind these effects remain poorly understood. This paper leverages US data on pregnancy intention to study the role of unwanted fertility in the observed birth order patterns. We document that children higher in the birth order are much more likely to be unwanted, in the sense that they were conceived at a time when the family was not planning to have additional children. Being an unwanted child is associated with negative life cycle outcomes as it implies a disruption in parental plans for optimal human capital investment. We show that the increasing prevalence of unwantedness across birth order explains a substantial part of the documented birth order effects in education and employment. Consistent with this mechanism, we document no birth order effects in families who have more control over their own fertility.

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research papers about birth order

Births that are Later-than-Desired: Correlates and Consequences

Caroline Sten Hartnett & Rachel Margolis

Selection Bias in the Link Between Child Wantedness and Child Survival: Theory and Data From Matlab, Bangladesh

David Bishai, Abdur Razzaque, … Michelle Hindin

research papers about birth order

Trajectories of Unintended Fertility

Sowmya Rajan, S. Philip Morgan, … Karen Benjamin Guzzo

We follow the demographic definition of an unwanted birth as a birth in excess of total desired fertility. The broader notion of unintended birth includes both unwanted and mistimed births. Given our purposes, we do not consider mistimed births.

The birth order literature is more limited in developing countries so little is known about how these patterns generalize to that context. For a few exceptions, see Birdsall ( 1979 , 1990 ), Behrman( 1988 ), Horton ( 1988 ), Ejrnæs and Pörtner ( 2004 ), Edmonds ( 2006 ) and De Haan et al. ( 2014 )

See Kessler ( 1991 ) for additional early references.

See among others (Baydar 1995 ; Kubička et al. 1995 ; Myhrman et al. 1995 ).

The indicator is not defined for those who reported being out of labor force for the entire year.

Children who result from mistimed pregnancies, particularly when these occur before marriage, may also have negative effects on outcomes later in life. See, for example, (Nguyen 2018 )

Joyce et al. ( 2002 ) find that prospective and retrospective reports of pregnancy intention provide the same estimate of the effects of being an unintended child on various prenatal outcomes once they control for selective pregnancy recognition using an IV procedure. Further, they show that the extent of unwanted fertility was the same regardless of whether the assessment was during pregnancy or after birth. They show this for a subsample of women for whom pregnancy intention was assessed both prospectively (during pregnancy) and retrospectively (after birth).

In principle, since we are looking at families with two and three children, the number of first-born and second-born children should be the same. In practice however, our number of second-born children is slightly smaller than the number of first-borns because they are more likely to have missing information on our outcome of interest, completed education.

However, it is of interest to explore whether the pattern of increasing prevalence of unwanted children across birth order holds in 4-child families. Since we only know whether the first, last, or second to last child in a family was unwanted, we cannot tell whether a second-born child in a four-child family was unwanted. But we can still look at first-, third-, and fourth-born children in those families. Consistent with the patterns in Table  2 , we find that in four-child families, the incidence of unwanted children grows from 16% among first-borns, to 27% among third-borns to a whopping 53% among fourth-borns.

These are families for which we identify at least one unwanted child or families for which information for pregnancy status is missing for at least one child.

We follow the religion taxonomy in Evans ( 2002 ) and classify the following religions as having a more strict attitude against abortion: Roman Catholic, Protestant, other Protestant, other Non-Christian, Latter Day Saints, Mormon, Jehovah’s Witnesses, Greek/Russian/Eastern Orthodox, Lutheran, Christian, Christian Science, Seventh Day Adventist, Pentecostal, Jewish, Amish, and Mennonite. Mothers reporting these religions are more likely to be pro-life and less likely to use abortion to terminate unwanted pregnancies. We then classify Baptists, Episcopalians, Methodists, Presbyterians, and Unitarians along with Agnostics and Atheists as having a less strict attitude towards abortion.

In the pooled specification, the effects for the third child are statistically significantly different from each other across the two tables.

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We thank Janet Currie, Joe Doyle, Martha Bailey and seminar participants at the University of Michigan for helpful comments. Lin acknowledges research support from the National Natural Science Foundation of China (Grant No.71573004) and the Key Laboratory of Mathematical Economics and Quantitative Finance (Peking University), Ministry of Education. During work on this project, Sun was supported in part by the George Katona Economic Behavior Research Award funded by the Institute for Social Research at the University of Michigan. All errors remain our own. The authors would like to thank the anonymous referees for helpful comments and suggestions.

Wanchuan Lin acknowledges research support from the National Natural Science Foundation of China (Grant No.71573004) and the Key Laboratory of Mathematical Economics and Quantitative Finance (Peking University), Ministry of Education. Shuqiao Sun was supported by the George Katona Economic Behavior Research Award, funded by the Institute for Social Research at the University of Michigan.

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Lin, W., Pantano, J. & Sun, S. Birth order and unwanted fertility. J Popul Econ 33 , 413–440 (2020). https://doi.org/10.1007/s00148-019-00747-4

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Why Your Big Sister Resents You

“Eldest daughter syndrome” assumes that birth order shapes who we are and how we interact. Does it?

An illustration of four nesting dolls in a row in a blue background. In descending height from left to right, the dolls have faces descending in age, with the one on the far right in white diapers with hands clasped at the front. Compared with the other dolls’ faces that look happy, the face of the doll on the far left looks sad. It is adorned with medals and a ribbon that says “1.”

By Catherine Pearson

Catherine Pearson is a younger daughter who still leans on her older sister for guidance all the time.

In a TikTok video that has been watched more than 6 million times, Kati Morton, a licensed marriage and family therapist in Santa Monica, Calif., lists signs that she says can be indicative of “eldest daughter syndrome.”

Among them: an intense feeling of familial responsibility, people-pleasing tendencies and resentment toward your siblings and parents.

On X, a viral post asks : “are u happy or are u the oldest sibling and also a girl”?

Firstborn daughters are having a moment in the spotlight , at least online, with memes and think pieces offering a sense of gratification to responsible, put-upon big sisters everywhere. But even mental health professionals like Ms. Morton — herself the youngest in her family — caution against putting too much stock in the psychology of sibling birth order, and the idea that it shapes personality or long term outcomes.

“People will say, ‘It means everything!’ Other people will say, ‘There’s no proof,’” she said, noting that eldest daughter syndrome (which isn’t an actual mental health diagnosis) may have as much to do with gender norms as it does with birth order. “Everybody’s seeking to understand themselves, and to feel understood. And this is just another page in that book.”

What the research says about birth order

The stereotypes are familiar to many of us: Firstborn children are reliable and high-achieving; middle children are sociable and rebellious (and overlooked); and youngest children are charming and manipulative.

Studies have indeed found ties between a person’s role in the family lineup and various outcomes, including educational attainment and I.Q . (though those scores are not necessarily reliable measures of intelligence ), financial risk tolerance and even participation in dangerous sports . But many studies have focused on a single point in time, cautioned Rodica Damian, a social-personality psychologist at the University of Houston. That means older siblings may have appeared more responsible or even more intelligent simply because they were more mature than their siblings, she said, adding that the sample sizes in most birth order studies have also been relatively small.

In larger analyses, the link between birth order and personality traits appears much weaker. A 2015 study looking at more than 20,000 people in Germany, the United Kingdom and the United States found no link between birth order and personality characteristics — though the researchers did find evidence that older children have a slight advantage in I.Q. (So, eldest daughters, take your bragging rights where you can get them.)

Dr. Damian worked on a different large-scale study, also published in 2015 , that included more than 370,000 high schoolers in the United States. It found slight differences in personality and intelligence, but the differences were so small, she said, that they were essentially meaningless. Dr. Damian did allow that cultural practices such as property or business inheritance (which may go to the first born) might affect how birth order influences family dynamics and sibling roles.

Still, there is no convincing some siblings who insist their birth order has predestined their role in the family.

After her study published, Dr. Damian appeared on a call-in radio show. The lines flooded with listeners who were delighted to tell her how skewed her findings were.

“Somebody would say: ‘You’re wrong! I’m a firstborn and I’m more conscientious than my siblings!’ And then someone else would call in and say, ‘You’re wrong, I’m a later-born and I’m more conscientious than my siblings!” she said.

What personal experience says

Sara Stanizai, a licensed marriage and family therapist in Long Beach, Calif., runs a virtual group with weekly meet-ups, where participants reflect on how they believe their birth order has affected them and how it may be continuing to shape their romantic lives, friendships and careers.

The program was inspired by Ms. Stanizai’s experience as an eldest daughter in an Afghan-American family, where she felt “parentified” and “overly responsible” for her siblings — in part because she was older, and in part because she was a girl .

While Ms. Stanizai acknowledged that the research around birth order is mixed, she finds it useful for many of her clients to reflect on their birth order and how they believe it shaped their family life — particularly if they felt hemmed in or saddled by certain expectations.

Her therapy groups spend time reflecting on questions like: How does my family see me? How do I see myself? Can we talk about any discrepancies in our viewpoints, and how they shape family dynamics? For instance, an older sibling might point out that he or she is often the one to plan family vacations. A younger sibling might point out that he or she often feels pressured into going along with whatever the rest of the group wants.

Whether or not there is evidence that birth order determines personality traits is almost beside the point, experts acknowledged.

“I think people are just looking for meaning and self-understanding,” Ms. Stanizai said. “Horoscopes, birth order, attachment styles” are just a few examples, she said. “People are just looking for a set of code words and ways of describing their experiences.”

Catherine Pearson is a Times reporter who writes about families and relationships. More about Catherine Pearson

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An Investigation of the Connection between Parenting Styles, Birth Order, Personality, and Sibling Relationships

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Sibling relationship is one of the longest relationships in human life and play a major role since some skills such as nurturance, caretaking, and meeting their own needs and those of other people around them (e.g. spouse, children, and parents) are fostered through sibling interaction. Several studies have been conducted among adults to identify the factors associated with sibling relationships. Despite its seeming importance, only a few researchers have focused on the role of personality type in sibling relationships. The current study examined whether Big-Five personality traits were associated with the quality of sibling relationships among young adults. Participants included 552 university students living in the United States of America (54% female and 46% male) aged 18 to 25 years. Participants completed the Lifespan Sibling Relationship Scale and the Big Five Inventory. A series regression analyses revealed that all personality traits were significantly associated with the quality of sibling relationships after controlling participant's gender and gender constellation. Of the personality traits, agreeableness was the strongest predictor of quality of sibling relationships. The current study's strengths and limitations and the implications future research are discussed.

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The size of the family influences the personality pattern both directly and indirectly. Directly, it determines what role the person will play in the family constellation, what kind of relationship he will have with other family members, and to a large extent, what opportunities he will have to make the most of his native abilities. Indirectly, family size influences the personality pattern through the kind of home climate fostered by families of different sizes and by the attitudes of the most significant members of the family toward the person. Another aspect of the connection between family size and personality is the amount of understanding and empathy found in families of different sizes. In a small family, parents have time to empathize with their children and to communicate with them. In a large family, there is less time, and also, as the number of children increases, the gap between the generations grows wider. This combination of conditions tends to lead to less warmth and...

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What the data says about abortion in the U.S.

Pew Research Center has conducted many surveys about abortion over the years, providing a lens into Americans’ views on whether the procedure should be legal, among a host of other questions.

In a  Center survey  conducted nearly a year after the Supreme Court’s June 2022 decision that  ended the constitutional right to abortion , 62% of U.S. adults said the practice should be legal in all or most cases, while 36% said it should be illegal in all or most cases. Another survey conducted a few months before the decision showed that relatively few Americans take an absolutist view on the issue .

Find answers to common questions about abortion in America, based on data from the Centers for Disease Control and Prevention (CDC) and the Guttmacher Institute, which have tracked these patterns for several decades:

How many abortions are there in the U.S. each year?

How has the number of abortions in the u.s. changed over time, what is the abortion rate among women in the u.s. how has it changed over time, what are the most common types of abortion, how many abortion providers are there in the u.s., and how has that number changed, what percentage of abortions are for women who live in a different state from the abortion provider, what are the demographics of women who have had abortions, when during pregnancy do most abortions occur, how often are there medical complications from abortion.

This compilation of data on abortion in the United States draws mainly from two sources: the Centers for Disease Control and Prevention (CDC) and the Guttmacher Institute, both of which have regularly compiled national abortion data for approximately half a century, and which collect their data in different ways.

The CDC data that is highlighted in this post comes from the agency’s “abortion surveillance” reports, which have been published annually since 1974 (and which have included data from 1969). Its figures from 1973 through 1996 include data from all 50 states, the District of Columbia and New York City – 52 “reporting areas” in all. Since 1997, the CDC’s totals have lacked data from some states (most notably California) for the years that those states did not report data to the agency. The four reporting areas that did not submit data to the CDC in 2021 – California, Maryland, New Hampshire and New Jersey – accounted for approximately 25% of all legal induced abortions in the U.S. in 2020, according to Guttmacher’s data. Most states, though,  do  have data in the reports, and the figures for the vast majority of them came from each state’s central health agency, while for some states, the figures came from hospitals and other medical facilities.

Discussion of CDC abortion data involving women’s state of residence, marital status, race, ethnicity, age, abortion history and the number of previous live births excludes the low share of abortions where that information was not supplied. Read the methodology for the CDC’s latest abortion surveillance report , which includes data from 2021, for more details. Previous reports can be found at  stacks.cdc.gov  by entering “abortion surveillance” into the search box.

For the numbers of deaths caused by induced abortions in 1963 and 1965, this analysis looks at reports by the then-U.S. Department of Health, Education and Welfare, a precursor to the Department of Health and Human Services. In computing those figures, we excluded abortions listed in the report under the categories “spontaneous or unspecified” or as “other.” (“Spontaneous abortion” is another way of referring to miscarriages.)

Guttmacher data in this post comes from national surveys of abortion providers that Guttmacher has conducted 19 times since 1973. Guttmacher compiles its figures after contacting every known provider of abortions – clinics, hospitals and physicians’ offices – in the country. It uses questionnaires and health department data, and it provides estimates for abortion providers that don’t respond to its inquiries. (In 2020, the last year for which it has released data on the number of abortions in the U.S., it used estimates for 12% of abortions.) For most of the 2000s, Guttmacher has conducted these national surveys every three years, each time getting abortion data for the prior two years. For each interim year, Guttmacher has calculated estimates based on trends from its own figures and from other data.

The latest full summary of Guttmacher data came in the institute’s report titled “Abortion Incidence and Service Availability in the United States, 2020.” It includes figures for 2020 and 2019 and estimates for 2018. The report includes a methods section.

In addition, this post uses data from StatPearls, an online health care resource, on complications from abortion.

An exact answer is hard to come by. The CDC and the Guttmacher Institute have each tried to measure this for around half a century, but they use different methods and publish different figures.

The last year for which the CDC reported a yearly national total for abortions is 2021. It found there were 625,978 abortions in the District of Columbia and the 46 states with available data that year, up from 597,355 in those states and D.C. in 2020. The corresponding figure for 2019 was 607,720.

The last year for which Guttmacher reported a yearly national total was 2020. It said there were 930,160 abortions that year in all 50 states and the District of Columbia, compared with 916,460 in 2019.

  • How the CDC gets its data: It compiles figures that are voluntarily reported by states’ central health agencies, including separate figures for New York City and the District of Columbia. Its latest totals do not include figures from California, Maryland, New Hampshire or New Jersey, which did not report data to the CDC. ( Read the methodology from the latest CDC report .)
  • How Guttmacher gets its data: It compiles its figures after contacting every known abortion provider – clinics, hospitals and physicians’ offices – in the country. It uses questionnaires and health department data, then provides estimates for abortion providers that don’t respond. Guttmacher’s figures are higher than the CDC’s in part because they include data (and in some instances, estimates) from all 50 states. ( Read the institute’s latest full report and methodology .)

While the Guttmacher Institute supports abortion rights, its empirical data on abortions in the U.S. has been widely cited by  groups  and  publications  across the political spectrum, including by a  number of those  that  disagree with its positions .

These estimates from Guttmacher and the CDC are results of multiyear efforts to collect data on abortion across the U.S. Last year, Guttmacher also began publishing less precise estimates every few months , based on a much smaller sample of providers.

The figures reported by these organizations include only legal induced abortions conducted by clinics, hospitals or physicians’ offices, or those that make use of abortion pills dispensed from certified facilities such as clinics or physicians’ offices. They do not account for the use of abortion pills that were obtained  outside of clinical settings .

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A line chart showing the changing number of legal abortions in the U.S. since the 1970s.

The annual number of U.S. abortions rose for years after Roe v. Wade legalized the procedure in 1973, reaching its highest levels around the late 1980s and early 1990s, according to both the CDC and Guttmacher. Since then, abortions have generally decreased at what a CDC analysis called  “a slow yet steady pace.”

Guttmacher says the number of abortions occurring in the U.S. in 2020 was 40% lower than it was in 1991. According to the CDC, the number was 36% lower in 2021 than in 1991, looking just at the District of Columbia and the 46 states that reported both of those years.

(The corresponding line graph shows the long-term trend in the number of legal abortions reported by both organizations. To allow for consistent comparisons over time, the CDC figures in the chart have been adjusted to ensure that the same states are counted from one year to the next. Using that approach, the CDC figure for 2021 is 622,108 legal abortions.)

There have been occasional breaks in this long-term pattern of decline – during the middle of the first decade of the 2000s, and then again in the late 2010s. The CDC reported modest 1% and 2% increases in abortions in 2018 and 2019, and then, after a 2% decrease in 2020, a 5% increase in 2021. Guttmacher reported an 8% increase over the three-year period from 2017 to 2020.

As noted above, these figures do not include abortions that use pills obtained outside of clinical settings.

Guttmacher says that in 2020 there were 14.4 abortions in the U.S. per 1,000 women ages 15 to 44. Its data shows that the rate of abortions among women has generally been declining in the U.S. since 1981, when it reported there were 29.3 abortions per 1,000 women in that age range.

The CDC says that in 2021, there were 11.6 abortions in the U.S. per 1,000 women ages 15 to 44. (That figure excludes data from California, the District of Columbia, Maryland, New Hampshire and New Jersey.) Like Guttmacher’s data, the CDC’s figures also suggest a general decline in the abortion rate over time. In 1980, when the CDC reported on all 50 states and D.C., it said there were 25 abortions per 1,000 women ages 15 to 44.

That said, both Guttmacher and the CDC say there were slight increases in the rate of abortions during the late 2010s and early 2020s. Guttmacher says the abortion rate per 1,000 women ages 15 to 44 rose from 13.5 in 2017 to 14.4 in 2020. The CDC says it rose from 11.2 per 1,000 in 2017 to 11.4 in 2019, before falling back to 11.1 in 2020 and then rising again to 11.6 in 2021. (The CDC’s figures for those years exclude data from California, D.C., Maryland, New Hampshire and New Jersey.)

The CDC broadly divides abortions into two categories: surgical abortions and medication abortions, which involve pills. Since the Food and Drug Administration first approved abortion pills in 2000, their use has increased over time as a share of abortions nationally, according to both the CDC and Guttmacher.

The majority of abortions in the U.S. now involve pills, according to both the CDC and Guttmacher. The CDC says 56% of U.S. abortions in 2021 involved pills, up from 53% in 2020 and 44% in 2019. Its figures for 2021 include the District of Columbia and 44 states that provided this data; its figures for 2020 include D.C. and 44 states (though not all of the same states as in 2021), and its figures for 2019 include D.C. and 45 states.

Guttmacher, which measures this every three years, says 53% of U.S. abortions involved pills in 2020, up from 39% in 2017.

Two pills commonly used together for medication abortions are mifepristone, which, taken first, blocks hormones that support a pregnancy, and misoprostol, which then causes the uterus to empty. According to the FDA, medication abortions are safe  until 10 weeks into pregnancy.

Surgical abortions conducted  during the first trimester  of pregnancy typically use a suction process, while the relatively few surgical abortions that occur  during the second trimester  of a pregnancy typically use a process called dilation and evacuation, according to the UCLA School of Medicine.

In 2020, there were 1,603 facilities in the U.S. that provided abortions,  according to Guttmacher . This included 807 clinics, 530 hospitals and 266 physicians’ offices.

A horizontal stacked bar chart showing the total number of abortion providers down since 1982.

While clinics make up half of the facilities that provide abortions, they are the sites where the vast majority (96%) of abortions are administered, either through procedures or the distribution of pills, according to Guttmacher’s 2020 data. (This includes 54% of abortions that are administered at specialized abortion clinics and 43% at nonspecialized clinics.) Hospitals made up 33% of the facilities that provided abortions in 2020 but accounted for only 3% of abortions that year, while just 1% of abortions were conducted by physicians’ offices.

Looking just at clinics – that is, the total number of specialized abortion clinics and nonspecialized clinics in the U.S. – Guttmacher found the total virtually unchanged between 2017 (808 clinics) and 2020 (807 clinics). However, there were regional differences. In the Midwest, the number of clinics that provide abortions increased by 11% during those years, and in the West by 6%. The number of clinics  decreased  during those years by 9% in the Northeast and 3% in the South.

The total number of abortion providers has declined dramatically since the 1980s. In 1982, according to Guttmacher, there were 2,908 facilities providing abortions in the U.S., including 789 clinics, 1,405 hospitals and 714 physicians’ offices.

The CDC does not track the number of abortion providers.

In the District of Columbia and the 46 states that provided abortion and residency information to the CDC in 2021, 10.9% of all abortions were performed on women known to live outside the state where the abortion occurred – slightly higher than the percentage in 2020 (9.7%). That year, D.C. and 46 states (though not the same ones as in 2021) reported abortion and residency data. (The total number of abortions used in these calculations included figures for women with both known and unknown residential status.)

The share of reported abortions performed on women outside their state of residence was much higher before the 1973 Roe decision that stopped states from banning abortion. In 1972, 41% of all abortions in D.C. and the 20 states that provided this information to the CDC that year were performed on women outside their state of residence. In 1973, the corresponding figure was 21% in the District of Columbia and the 41 states that provided this information, and in 1974 it was 11% in D.C. and the 43 states that provided data.

In the District of Columbia and the 46 states that reported age data to  the CDC in 2021, the majority of women who had abortions (57%) were in their 20s, while about three-in-ten (31%) were in their 30s. Teens ages 13 to 19 accounted for 8% of those who had abortions, while women ages 40 to 44 accounted for about 4%.

The vast majority of women who had abortions in 2021 were unmarried (87%), while married women accounted for 13%, according to  the CDC , which had data on this from 37 states.

A pie chart showing that, in 2021, majority of abortions were for women who had never had one before.

In the District of Columbia, New York City (but not the rest of New York) and the 31 states that reported racial and ethnic data on abortion to  the CDC , 42% of all women who had abortions in 2021 were non-Hispanic Black, while 30% were non-Hispanic White, 22% were Hispanic and 6% were of other races.

Looking at abortion rates among those ages 15 to 44, there were 28.6 abortions per 1,000 non-Hispanic Black women in 2021; 12.3 abortions per 1,000 Hispanic women; 6.4 abortions per 1,000 non-Hispanic White women; and 9.2 abortions per 1,000 women of other races, the  CDC reported  from those same 31 states, D.C. and New York City.

For 57% of U.S. women who had induced abortions in 2021, it was the first time they had ever had one,  according to the CDC.  For nearly a quarter (24%), it was their second abortion. For 11% of women who had an abortion that year, it was their third, and for 8% it was their fourth or more. These CDC figures include data from 41 states and New York City, but not the rest of New York.

A bar chart showing that most U.S. abortions in 2021 were for women who had previously given birth.

Nearly four-in-ten women who had abortions in 2021 (39%) had no previous live births at the time they had an abortion,  according to the CDC . Almost a quarter (24%) of women who had abortions in 2021 had one previous live birth, 20% had two previous live births, 10% had three, and 7% had four or more previous live births. These CDC figures include data from 41 states and New York City, but not the rest of New York.

The vast majority of abortions occur during the first trimester of a pregnancy. In 2021, 93% of abortions occurred during the first trimester – that is, at or before 13 weeks of gestation,  according to the CDC . An additional 6% occurred between 14 and 20 weeks of pregnancy, and about 1% were performed at 21 weeks or more of gestation. These CDC figures include data from 40 states and New York City, but not the rest of New York.

About 2% of all abortions in the U.S. involve some type of complication for the woman , according to an article in StatPearls, an online health care resource. “Most complications are considered minor such as pain, bleeding, infection and post-anesthesia complications,” according to the article.

The CDC calculates  case-fatality rates for women from induced abortions – that is, how many women die from abortion-related complications, for every 100,000 legal abortions that occur in the U.S .  The rate was lowest during the most recent period examined by the agency (2013 to 2020), when there were 0.45 deaths to women per 100,000 legal induced abortions. The case-fatality rate reported by the CDC was highest during the first period examined by the agency (1973 to 1977), when it was 2.09 deaths to women per 100,000 legal induced abortions. During the five-year periods in between, the figure ranged from 0.52 (from 1993 to 1997) to 0.78 (from 1978 to 1982).

The CDC calculates death rates by five-year and seven-year periods because of year-to-year fluctuation in the numbers and due to the relatively low number of women who die from legal induced abortions.

In 2020, the last year for which the CDC has information , six women in the U.S. died due to complications from induced abortions. Four women died in this way in 2019, two in 2018, and three in 2017. (These deaths all followed legal abortions.) Since 1990, the annual number of deaths among women due to legal induced abortion has ranged from two to 12.

The annual number of reported deaths from induced abortions (legal and illegal) tended to be higher in the 1980s, when it ranged from nine to 16, and from 1972 to 1979, when it ranged from 13 to 63. One driver of the decline was the drop in deaths from illegal abortions. There were 39 deaths from illegal abortions in 1972, the last full year before Roe v. Wade. The total fell to 19 in 1973 and to single digits or zero every year after that. (The number of deaths from legal abortions has also declined since then, though with some slight variation over time.)

The number of deaths from induced abortions was considerably higher in the 1960s than afterward. For instance, there were 119 deaths from induced abortions in  1963  and 99 in  1965 , according to reports by the then-U.S. Department of Health, Education and Welfare, a precursor to the Department of Health and Human Services. The CDC is a division of Health and Human Services.

Note: This is an update of a post originally published May 27, 2022, and first updated June 24, 2022.

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Support for legal abortion is widespread in many countries, especially in Europe

Nearly a year after roe’s demise, americans’ views of abortion access increasingly vary by where they live, by more than two-to-one, americans say medication abortion should be legal in their state, most latinos say democrats care about them and work hard for their vote, far fewer say so of gop, positive views of supreme court decline sharply following abortion ruling, most popular.

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Embryo Development and Selection: Advances in Genetics

Editorial: Embryo Development and Selection: Advances in Genetics Provisionally Accepted

  • 1 Guilin Medical University, China
  • 2 Hainan Medical University, China

The final, formatted version of the article will be published soon.

Assisted reproductive technologies (ART) are being utilized with increasing frequency across the globe to support individuals who face challenges in conceiving naturally. ART procedures facilitate pregnancy by extracting eggs from a woman's ovaries, fusing them with sperm in a laboratory setting, and subsequently reintroducing them into the woman's body. The efficacy of ART is subject to a multitude of factors, encompassing genetic considerations, historical medical and reproductive data, the specific medications employed during ART treatment, and any complications that may arise during pregnancy. The focus of this research topic is the selection of embryos during the ART process, and an exploration of the factors that influence embryo development and the overall success rate of ART. 1. Abu et al. evaluated the impact of supplementing a single-dose GnRH agonist to the standard progestogen regimen for luteal phase support in IVF treatments. Compared to using progestogens alone, they found that adding a GnRH agonist improved the overall IVF outcomes.2. Andreescu has conducted a review on the dysregulation of immune responses between the mother and fetus, a factor that heightens the risk of embryo rejection and reproductive failure.This paper provides an exhaustive overview of the current literature on the influence of Calcineurin inhibitors and anti-TNF treatment in enhancing the live birth rate post embryo transfer. It concludes that the suppression of immunological rejection and the promotion of immunological tolerance are vital in safeguarding embryos and averting immunological assaults. Therefore, it is important to exercise caution while selecting use of any immunosuppressive therapy in pregnancy. indicates that the risks associated with angular pregnancy following ART may not be as severe as previously thought. With regular, close monitoring, the majority of these cases can be managed expectantly, often resulting in live births. 5. Zhu and colleagues conducted a study to identify the risk factors that influence the occurrence of heterotopic pregnancies following IVF-ET. They also examined the outcomes of pregnancies after surgical intervention for heterotopic pregnancies. Their research indicates that a history of ectopic pregnancy, multiple abortions, tubal infertility, and multiple-embryo transfer may significantly increase the risk of a subsequent heterotopic pregnancy after IVF-ET.The study also found that for patients with heterotopic pregnancies who undergo surgery, factors such as a shorter operation duration, a smaller ectopic mass, and a location in the ampulla of the fallopian tube are associated with a more favorable reproductive prognosis. IVF success rates are influenced by a multitude of factors, including genetic considerations, historical medical and reproductive data, the types of medications used during ART treatment, and complications that may arise during pregnancy. The research papers discussed here offer significant insights into improving the success rates of IVF. They underscore the efficacy of a combined treatment approach using N-Acetylcysteine and Gonadotropins, which has been shown to enhance ovarian response to superovulation drugs and improve the quality of blastocysts in older women. The papers also identify surgical time, the size of ectopic masses, and their location in the ampulla of the fallopian tube as key factors in determining the reproductive prognosis in patients with ectopic pregnancies. Additionally, the use of GnRH agonists in the luteal phase has been found to increase IVF success rates. The papers also discuss the evaluation of cornual pregnancy following ART. The aim of these studies is to reduce the risks associated with assisted reproduction and increase pregnancy rates, thereby providing invaluable information for clinical IVF centers. The referenced studies investigate the influence of several factors on the success rate of IVF. These factors encompass the patient's medical history, the treatment protocol, the medications administered during treatment, and complications encountered during pregnancy.The insights and research outcomes presented are of immense value for improving the success rates of assisted reproductive techniques.

Keywords: assisted reproductive technologies, Pregnancy rates, Embryo development, Embryo selection, Influence factor

Received: 13 Apr 2024; Accepted: 22 Apr 2024.

Copyright: © 2024 Liu and Ma. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Mx. Yanlin Ma, Hainan Medical University, Haikou, 571199, Hainan Province, China

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Ordered Delinquency: The “Effects” of Birth Order On Delinquency

Patrick r. cundiff.

The Pennsylvania State University

Juvenile delinquency has long been associated with birth order in popular culture. While images of the middle child acting out for attention or the rebellious youngest child readily spring to mind, little research has attempted to explain why. Drawing from Adlerian birth order theory and Sulloway's born to rebel hypothesis I examine the relationship between birth order and a variety of delinquent outcomes during adolescence. Following some recent research on birth order and intelligence, I use new methods that allow for the examination of both between-individual and within-family differences to better address the potential spurious relationship. My findings suggest that contrary to popular belief the relationship between birth order and delinquency is spurious. Specifically, I find that birth order effects on delinquency are spurious and largely products of the analytic methods used in previous tests of the relationship. The implications of this finding are discussed.


Social scientists have long shown the effects of birth order and family size on outcomes such as intelligence and educational achievement, but little attention has been paid to these effects on deviance and delinquency. This research tests competing hypotheses of the effects of birth order on delinquency and other problem behaviors in adolescence derived primarily from Adler's birth order theory and Sulloway's born to rebel hypothesis. As I review in more detail below, birth order theory, as proposed by Adler (1928) , suggests a curvilinear relationship in which firstborns or single children 1 would score the lowest on a delinquency scale, middleborns would score the highest, and the youngest children should score somewhere between firstborns and middleborns. More recently, Sulloway (1996) , building upon Adler's work, has argued that laterborns 2 are more likely to rebel than firstborns. While Sulloway's historical analysis specifically looked at participation in scientific revolution, more recent research has examined his hypothesis using outcomes of participation in protests and marijuana use (see also Zeigenhaft, 2002 ; Zweigenhaft & Von Ammon, 2000 )

I use data from the National Longitudinal Study of Adolescent Health (Add Health) to examine the effects of birth order on delinquency. Unlike previous research, I use a large nationally representative dataset to better identify and parse out the effects, if any, of birth order on delinquency, as well as the underlying mechanisms for these associations. Furthermore, I examine both between-individual and within-family differences in the effects of birth order on delinquency to better address potential spurious relationships. I begin with a review of Adler's and Sulloway's theoretical perspectives.

Theoretical Perspectives

Adler's (1928) seminal work “Characteristics of the First, Second, Third Child” provided the basis of birth order theory. Adler argued that the first child has one of two paths: the “path of the single child” or the “path to dethronement.” For example, if a first born child remains a single child, he or she will more than likely remain the center of attention. The constant attention from parents generates expedited development, which in turn makes the child self-confident. However, the child is also prone to developing a “spoiled” or entitled attitude. On the other hand, the arrival of a sibling can be a traumatic experience for a first born as the child suffers dethronement, so that the child is no longer the center of attention. The path to dethronement causes the first child to determinedly attempt to reclaim the center of attention, which results in conformity to conventional goals and values. Moreover, the younger child thrives in his or her ordinal position as desires and ambitions are nurtured and cultivated by the parents. This nourishment leads the second child to become “more charming and likeable than their older sibling” ( Adler, 1928 : 24). Nevertheless, the younger child is not without trials as he or she is constantly in competition with a larger and more intelligent rival.

According to Adler, the arrival of the third sibling, however, does not dramatically shift the balance of power. The third child receives similar treatment to the second child, but the youngest child is generally more apt to overcome the competition between siblings and to establish his or her importance in the family. If the third child is unable to compete, he or she will seek the center of attention through maintaining a prince or princess mentality. Adler argued that this mentality will lead to laziness, shirking of responsibilities, and generating elaborate excuses. Sibling rivalries tend to be fueled by the competition over parental resources, this competition can become strain inducing, causing jealousy among the sibship.

Since the inception of Adler's birth order theory, a sizable body of research has found varying and contradictory evidence regarding the effects of birth order on adolescent adjustment. Most of this research has centered on achievement ( Adams, 1972 ; Adams & Phillips, 1972 ; Altus, 1966 ; Black, Devereux, & Salvanes, 2005 ; Booth & Kee 2009 ; Forer, 1976 ; Kessler, 1991 ), intelligence ( Black et al., 2007 ), creativity ( Runco & Bahleda, 1987 ), conformity ( Becker & Carroll, 1962 ; Bragg & Allen, 1970 ; Sampson, 1962 ), and risk taking ( Eisenman, 1987 ; Nisbett, 1968 ; Sulloway & Zweigenhaft, 2010 ). Although empirical tests of birth order theory have generally produced mixed results, several consistent personality profiles have been built around each ordinal position. Forer (1969 , 1976 ), for instance, provided personality profiles and tendencies for a variety of ordinal positions and sibship 3 sex distributions. 4

Overall, Forer's (1976) descriptions focused primarily on single children, firstborns, middleborns, and youngest children. 5 Firstborns have a tendency to be more conservative and are also likely to be concerned with dealing with the pressures of upholding the family mores and attitudes. Baskett (1984) found that firstborns were more likely than other ordinal positions to receive negative responses from parents and other siblings following misconduct or failure. When a sibling is added, the firstborn may react with jealousy and anxiety following dethronement. As earlier noted, firstborn children tend crave and need parental approval, thus they can be prone to succumbing to parental pressure. Because the middleborn position stimulates maximum sibling competition; the stress and strain from the middle ordinal position can either lead to great success in life or constant failure. Moreover, due to the divided parental attention, middle children may have difficulties in adjustment and role identification. Thus, middleborns would be theorized to have the highest likelihood of having social problems with peers and figures of authority. Forer's personality profiles tend to indicate that middleborn children are the most prone to difficulties in conventional achievement. Research conducted by Blau and Duncan (1967) found that children occupying polar ordinal positions tended to have more successful careers than middleborn children. Research by Tygart (1991) proposed that a curvilinear relationship between birth order and delinquency could be a result of middle children lacking parental attention or supervision, thus forcing middle children to seek attention or approval from their peer group. Through a process of social learning within the peer group, middle children utilize delinquency to gain attention and approval. The youngest child typically is recognized as the baby of the family regardless of maturation, and this role is both advantageous and disadvantageous. While the youngest child is characterized as more extroverted than older siblings, youngest children generally tend to have low acceptance of responsibility.

More recently, Sulloway (1996) found a significant birth order effect upon the propensity to rebel. In Born to Rebel , he found that laterborns were more likely than firstborns to engage in rebellious activities, based upon his analysis of thousands of historical figures. Sulloway's findings have since garnered support by several more contemporary studies ( Healey & Ellis, 2007 ; Paulhus et al., 1999 ; Salmon & Daly, 1998 ; Zweigenhaft, 2002 ; Zweigenhaft & Von Ammon, 2000 ). Sulloway's theory begins with the assumption that siblings who are raised together typically have markedly different personalities, and these differences are comparable to differences observed between individuals not from the same family. Sulloway contends that these differences are shaped by competition over family resources, such as parental affection and parental resources. This competition creates rivalries among the siblings, as each child vies for the family's resources. The born to rebel hypothesis emphasizes the impact birth order plays upon family niches. Sulloway's findings point to rebelliousness as a possible mechanism behind the effects of birth order. Sulloway's construction of rebellion emphasized risk-taking and openness to radical change. Laterborns are seen as more open to risk-taking and radical change because these behaviors favor them in the competition for parental resources as it upsets the tradition associated with investment in the firstborn. While Sulloway does not speak directly about delinquency, it would follow that those open to radical change and those more willing to take risks may also be open to delinquency as a method of radical change.

The rebirth of interest into the effects of birth order has generated a considerable amount of literature in the fields of psychology and sociology, yet few studies have looked to reexamine the effects of birth order on delinquency. Using a sample of youth from Israel, Rahav (1980) found a curvilinear relationship between ordinal position and delinquency rates in which middle children scored the highest and oldest and youngest children scored lower. However, like other research on birth order effects, Rahav did not adequately address the potential spurious relationships between birth order and delinquency. Similarly, Argys et al. (2006) found evidence that middleborns and lastborns were more likely to use substances and engage in risky adolescent behavior (sexual activity). While Argys et al.'s findings were more robust than Rahav's (1980) , they still neglect issues plaguing much of birth order research. Using a French representative sample, Bègue and Roché (2005) observed a relationship between birth order and delinquency. The relationship was then largely mediated by the introduction of sibship size and parental supervision into the statistical model. Bègue and Roché (2005) concluded that birth order plays a moderate role in delinquency and that the effect is in part a product of differential parental supervision.

Within birth order research there has been a growing body of literature ( Capra & Dittes, 1962 ; Edwards & Klemmack, 1973 ; Ernst & Angst, 1983 ; Freese et al., 1999 ; Hauser & Sewell, 1985 ; Kammeyer, 1967 ; Schooler, 1972 ; Schooler, 1973; Seff et al., 2005; Steelman & Powell, 1985 ; Townsend, 2000 ) that suggests that the effects of birth order are artificial or negligible at best. This area of research has often focused on attempting to prove that observed effects of birth order are in fact spurious. Spuriousness results when the observed effects of a predictor variable are found to be the product of some other variable. Additional studies ( Capra & Dittes, 1962 ; Kammeyer, 1968) have also identified potential pitfalls when using birth order as a variable. Capra and Dittes (1962) identified severe sample biases associated with prior research on birth order. While findings from Kammeyer's (1968) study suggested that previous research attempted to utilize ordinal position beyond its capabilities and future research should attempt to extract the true effects of birth order by better controlling for possible confounding variables.

Birth order theory's strongest criticisms ( Ernst & Angst, 1983 ; Schooler, 1972 ; Steelman, 1985 ), however, have focused on methodology flaws and whether the effects of birth order are in fact causal. For instance, Schooler (1972) conducted a meta-analysis on birth order effects from previously published and unpublished studies and found that results from prior research reveal no reliable evidence of birth order effects. Schooler made note of several variables that should be accounted for: density of sibling spacing, sex of siblings, family size, and social class trends. Steelman and Powell (1985) found no significant relationship between birth order and academic performance and the conclusions lead them to believe that any observed birth order effects may be artificial.

Ernst and Angst (1983) delivered perhaps the most extensive analysis of birth order. Ernst and Angst tested birth order effects on all available fields (including: intelligence, school achievement, occupational status, personality, socialization, and mental illness) and their subsequent findings diminished the credibility of previous research. Their analysis found that in regards to school achievement and substance use (cigarettes and alcohol), birth order had negligible effects. Furthermore, birth order had no significant effects on intelligence or personality. Ernst and Angst further tested relationships between birth order and variables related to personality while controlling for structural and individual variables and found that birth order effects disappeared. Additionally, Ernst and Angst identified that general differences in scores were between subjects, not between siblings. While these criticisms focused on early works using birth order theory, few criticisms have focused specifically on Sulloway's (1996) “born to rebel” hypothesis. Recent analyses ( Freese et al., 1999 ; Zweigenhaft, 2002 ; Zweigenhaft & Von Ammon, 2000 ) have yielded mixed results. Both studies conducted by Zweigenhaft focused on rebellious activities (such as civil disobedience, participating in protests or demonstrations, and marijuana use) and found support for Sulloway's work, while Freese et al. failed to find the same support. Freese et al.'s (1999) analysis focused on examining Sulloway's contention that firstborns display more conservative attitudes, tough mindedness, and supportive attitudes towards authority. The analysis found no significant effects for Sulloway's contention, even stating that the nonsignificant coefficients were in the wrong direction.

In addition to tests of Sulloway's born to rebel hypothesis , many researchers ( Retherford & Sewell, 1991 ; Rodgers, 2001 ; Rodgers et al., 2000 ; Wichman et al., 2006 ; Wichman et al., 2007 ) have criticized previous literature's failure to examine within-family, or between siblings, differences when examining the effects of birth order and family size on intelligence (see Sulloway, 2007 and Kanazawa, 2012 for a full review of the previous literature on birth order and intelligence). Retherford and Sewell's work (1991) demonstrated that the use of within-family analyses provide a strikingly different result from works that focused on between-individual differences. In line with the work of Retherford and Sewell (1991) , Rodgers (2001) and Rodgers et al.'s (2000) work provided evidence suggesting that any birth order effects are a product of differences between families, not within. More recently, Wichman et al. (2006) utilized a multilevel approach in their examination of the effect of birth order on intelligence. They found that when controlling for maternal age, the effects of birth order on intelligence become negligible and statistically non-significant. Wichman et al. (2006) noted that “the fundamental cause of supposed birth order effects lies between, not within, families” (p. 125). In defense of birth order, Zajonc and Sulloway (2007) questioned the Wichman et al.'s study design and analyses. Zajonc and Sulloway provided analyses demonstrating that the effects of birth order are both a between individual and within family phenomenon. In reply to Zajonc and Sulloway's (2007) work, Wichman et al. (2007) contended that the research design by Zajonc and Sulloway failed to appropriately control for influences on intelligence that vary across families.

In summary, the evidence is mixed on whether the effects of birth order observed in previous studies are indeed causal. The greatest issue in evaluating the effects of birth order is the level of evaluation. Much of the recent criticisms have debated whether birth order should be evaluated between individuals or within families, and in line with this debate I test the effects of birth order at both of these levels. While I test the effect of birth order at each of these evaluation levels, the within-family evaluation models make more sense theoretically. Both Adlerian birth order theory and Sulloway's born to rebel hypothesis are inherently within family based. When an individual is a firstborn, or a middleborn, or a lastborn that ordinal position is relative to their own family, and their own sibship. The effects of birth order are thought by both perspectives to develop out of competition with siblings, thus testing the effects only between-individuals is in direct contrast to the theoretical underpinnings of both theoretical perspectives.

Current Study

This study examines the relationship between birth order and delinquency. Research examining the link between birth order and delinquency has become dated and there exists a growing body of literature focused on testing hypotheses generated by Sulloway's born to rebel hypothesis . The primary goal of this study is to sort out the influence, if any, that birth order has upon delinquency. If a relationship between birth order and delinquency exists, this study will then seek to clarify the mechanism(s) at work.

The following hypotheses are derived from the above theoretical perspectives of Adler's birth order theory and Sulloway's born to rebel hypothesis .

Hypothesis 1: Middleborn children will be more likely to engage in delinquency than either firstborn or lastborn children

If hypothesis 1 is confirmed, the results will lend support to birth order theory; which suggests that low achievement explains why middleborn children are more delinquent than firstborn and laterborn children.

Hypothesis 2: Firstborn children will be less likely to engage in delinquency than laterborn children

If hypothesis 2 is confirmed and hypothesis 1 is not confirmed, the results will lend support to Sulloway's born to rebel hypothesis. Recall that Sulloway argues that laterborns are the most likely to engage in delinquency because they have a tendency toward rebellion.

Hypothesis 3: The relationship between birth order and delinquency is spurious and a product of analytic method

Finally, if hypothesis 3 is confirmed, the results would lend support for studies that have questioned whether the effects of birth order are causal and the level of analysis.

These hypotheses will be tested using data from the National Longitudinal Study of Adolescent Health (Add Health). Add Health is a longitudinal study of a nationally representative sample of adolescents in grades 7 to 12. From 1994 to 2008, the study has collected four waves of data from the sample of adolescents, with additional surveys administered to parents, siblings, and school administrators. Since the effects of birth order are theorized to be established prior to adolescence, I do not use the follow-up data. Thus, this analysis focuses on only the wave 1 in-home survey data. Additionally, wave 1 has the largest sample size giving the analyses greater statistical power to detect even small effects of birth order on delinquency. Harris et al. (2008) sampled 80 high schools and 52 middle schools from the US with unequal probability of selection. Incorporating systematic sampling methods and implicit stratification into the Add Health study design ensured that this sample is representative of US schools with respect to region of country, urbanicity, school size, school type, and ethnicity. An in-school survey was administered during one 45-60 minute class period to all available students in each of the sampled schools; in-home interviews were then conducted approximately six months after the in-school survey to approximately 200 adolescents randomly selected from each school. Interviews lasted 90 minutes and were completed confidentially through the use of laptop computers and headphones. The respondent's parent(s) were also interviewed. Add Health yielded a response rate of 79 percent for wave 1. One of the strengths of this dataset is its sampling of sibling pairs. Sibling data was obtained purposefully if adolescents were found to have siblings within the study's age and grade ranges. The survey attempted to sample as many siblings as possible. The large number of sibships represented within the Add Health data provides me with a large number observations that can be used for the within family analytic models.

To maximize the amount of useable data I utilize multiple imputation methods to deal with missing data using Stata's ICE command. Using multiple imputation allows me to maximize my sample size as well as provide a more representative and powerful sample. Multiple imputation uses data as a placeholder, it fills in the many holes within a dataset that are attributable to missing data as well as adds variation to each hole filled (see Johnson & Young, 2011 ; Royston, 2005 for more information on multiple imputation). The sample following the use of multiple imputation methods contains approximately 14,884 adolescents in the between family sample and 3,802 adolescents in the within family sample. Comparisons between imputed and non-imputed data do not provide evidence of any significant statistical differences.

Outcome Variable

For the purposes of this study, I combine several measures of delinquency to create a problem behavior composite measure that indicates whether the adolescent engaged in marijuana use in the past 30 days or non-violent crime and binge drinking in the past year. The problem behavior composite measure has a Cronbach's alpha coefficient of 0.77 indicating that the components of the composite measure held together well. The problem behavior composite measure is composed of three general components marijuana use, non-violent crime and binge drinking. A list of the questions used for each of the items included in the problem behavior composite measure is included in the Appendix table . Responses to the questions were dichotomized to create each of the components of the composite measure. The problem behavior composite score was created by combining the responses of the three components and then dichotomizing the sum, where engagement in any of the problem behavior components was coded as “1” (and coded “0” if the adolescent had not engaged in any of the problem behavior components).

Predictor Variable

Birth order is the key predictor variable utilized in this study. Birth order information was obtained through the use of the following questions “Which child are you—the first, the second, or what?” and “How many children have your biological parents had together?” Responses to both questions ranged from 1-15. Based upon the responses to both questions, respondents were then coded into one of four categories: single child, firstborn, middleborn, or lastborn. From this variable two additional variables were also created, both of which excluded single children. Note that this exclusion is based upon the contention that single children and firstborn children generally have negligible differences ( Falbo 1984 , Polit and Falbo 1987 ). The birth order variable places adolescents into one of the three following categories: firstborn, middleborn, or lastborn. As the Add Health data contains adolescents that come from families that range in sibship size from 2-15 I utilize a categorization matrix to group adolescents into the three categories of the birth order variable. I present the birth order categorization matrix in Figure 1 . While I choose to focus on biological ordinal position previous research has noted functional ordinal position may also play a role in the relationship (see Sulloway, 1996 ). Often times biological and functional birth order are the same, however, in situations involving large age gaps between children, mortality, adoption, and remarriage these birth order constructs will differ. In the case of my study I excluded adolescents who were adopted and controlled for the effect of intact family to better attempt to control for the effect of functional order 6 .

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Potential Mediator Variables

Both Adlerian birth order theory and Sulloway's born to rebel hypothesis note that birth order effects originate from competition among siblings for parental resources. The competition for parental resources, then, offers potential mediators of parental presence and parental closeness. Competition among siblings for parental resources can often take place in an academic setting, in which siblings have a defined metric for success (i.e. GPA). Thus, I include measures of academic achievement and ability tap into this arena of competition for parental resources among siblings. In addition to the inclusion of these mediators being motivated by birth order theory, these potential mediators have also been linked to delinquency in previous research (see Barnes et al., 2006 and Katsiyannis et al., 2008 for full reviews). To address the hypothesized underlying mechanisms of birth order and delinquency, predictor variables indicating academic achievement, intellectual ability, parental monitoring, and parental closeness will be included in the analyses. The academic achievement measure is based upon grade point averages (GPA) constructed from self-reported grades in the following subjects: English, Mathematics, History or Social Sciences, and Science. The construction of the GPA variable is done through calculating the GPA for all courses in which each participant was enrolled. Thus, if a survey participant was enrolled in only two of the four subjects, his/her GPA score would reflect only those two courses. My calculation of GPA allows for GPA to range from 1.0 (D) to 4.0 (A). The picture vocabulary test (PVT) administered during the survey will serve as a measure of intellectual ability. Scores on the PVT ranged from 13 to 146. I standardized the PVT score by creating z-scores to give more meaning to the score.

The parental presence measure is based upon adolescent responses regarding the general presence of parents before they leave for school, when they return from school in the afternoon, when they eat dinner and when they go to bed in the evening. The responses ranged for presence before school, when they return from school, and when they go to bed ranged from always (coded as “5”) to never (coded as “1”). The max score between parents for each time point (morning, afternoon, and evening) was used in the calculation of parental presence. The responses for the frequency with which the adolescents ate dinner with at least one parent over the past seven days ranged from 0 to 7. The final parental presence measure was calculated by summing the max parental presence scores for morning, afternoon, and evening presences with the score from the frequency of eating dinner together in the past seven days; creating a distribution that ranged from 0 (indicating no parental presence) to 22 (indicating constant presence). The parental closeness measure is based upon responses to questions regarding how close a respondent feels to each parent and activities (shopping, sport, religious event, talked about problem, talked about social life, went to entertainment, talked about school, worked on school project, and talked about other school things) the individual has recently (within the past four weeks) done with a parent. The responses to the closeness and sum of activities done were summed together; the max parental closeness score (mother or father) is used for each adolescent. I include these mediating variables to explore the robustness of the effect of birth order on engagement in problem behavior.

Control Variables

The following variables will be used to control for possible confounding influences: sibship size, twin status, sex, race, family stability, parental education, family income and age. Sibship size was obtained using the following: “How many children have your biological parents had together?” Controlling for sibship size will help to reduce the effect of variance between subjects by limiting the effect that coming from a large or small family will have upon the outcome variables. While one could expect sibship size and birth order to be strongly correlated as adolescents from larger families necessarily have a greater chance of being classified as a middleborn, the correlation between the two variables is minute (r =0.07). The variable twin status was obtained through asking “Are you a twin?” It is necessary to control for the effects of twins due to the oversampling of twins conducted by Add Health. Intact family is determined by responses to questions regarding residences of parents; adolescents were coded for intact family as “1” if both biological parents were still residing with child, and “0” if either the biological mother or father were not residing with the child. Parental education was generated by using the maximum score of educational attainment score between the two parents; the scores ranged from 0 (no education) to 5 (professional degree). Family income information was gathered from the parent survey. The income question on the parent survey asked for total household income in the past year. Responses ranged from $0-$999,000, these responses were then grouped into income quintiles based on income quintiles observed in the US Census. Demographic variables of sex (coded as a dummy variable where a code of “1” indicates that the individual is female), race/ethnicity (coded as a series of dummy variables), and age will also be utilized to control for birth order effects upon delinquency. Table 1 provides descriptive statistics for both outcome and predictor variables used in this study (with the exclusion of single children). The table provides descriptive statistics for both the between family and within family samples. Comparisons of the descriptive statistics for the two samples reveal no statistically significant differences in the outcome variables between the two samples. Statistically significant differences did emerge between the samples for the twins variable, sibship size, and the proportions of firstborns, middleborns, and lastborns. These significant differences are a product of the more focused within-families sample design as twins were purposefully oversampled, and adolescents with more siblings had a greater chance of having another sibling be included in the AddHealth sample. While the differences are statistically significant, these differences do not appear to be substantively meaningful.

Analytic Strategy

The analytic strategy consists of examining the effects of birth order utilizing both between-individual and within-family analyses to assess genuine impacts of birth order on delinquency as well as the underlying mechanisms. First, I estimate a logistic regression examining the effects of birth order on the problem behavior composite measure. Logistic regression is better suited for cases involving a dichotomous outcome variable than OLS regression. The results of the logistic regression provide useful interpretations in that one unit changes in independent variables correspond to changes in the likelihood of an event. In the case of this study, I am interested in the effect of one unit changes in birth order on the probability of delinquency (for a full review of logistic regression techniques and logic see Pampel, 2000 ). These cross-sectional analyses capture any between-individual differences in the effects of birth order on delinquency. The cross-sectional analyses are consistent with much of the previous literature that have found significant birth order effects. Finally, in line with more recent research, I used fixed effects models to further analyze the significant relationship (if any) between birth order and the problem behavior composite measure. As birth order is conceptualized to be a within family process, it is necessary to examine the effects of birth order using a methodology that is able to control for family characteristics. Using a fixed effects analytic framework allows for the control of observed and unobserved family-stable characteristics (i.e. family income, parents' education, neighborhood, discipline style, etc…) that may be correlated with the problem behavior composite measure. Where previous research is lacking is in their control of family specific characteristics, observed and unobserved. Failure to control for these characteristics leaves the possibility of the effects of birth order being spurious open. Utilizing family-specific fixed effects allows for focus on within-family differences. The fixed effects methodology allows researchers to test causal claims with non-experimental data as each member of the sibship serves as a reference point to all other siblings (for a full review of fixed effects regression see Allison 2009 ).

The logistic regression fixed effects equation is presented below:

in which K is the number of family varying covariates, N is the total number of individuals, β 0 is the constant, y iz is a problem behavior for person i in family z , β k x izk is an observed value on the k th family-varying covariate, such as age or parental closeness, and ε u is the unobserved error. The equation was adapted from the standard fixed effects regression equation to study within family differences rather than within individual differences. The logistic regression fixed effects model was conducted in Stata using the XTLOGIT command. To insure the appropriateness of the use of fixed effects over random effects, Hausman tests were conducted ( Hausman 1978 ). Note that, for all outcomes examined in this thesis, the Hausman tests were found to be statistically significant. This indicates that the fixed effects models were more appropriate.

Examining the Effects of Birth Order on Delinquency: Between-Individual Analyses

Table 2 provides the results of the logistic regression testing the effects of birth order on the problem behavior composite measure. Model 1 indicates that both middleborns and lastborns are significantly more likely to have engaged in problem behaviors in the past 12 months than firstborns net of controls (odds ratios of 1.33 and 1.20, respectively). Odds ratios offer comparable effect sizes for each variable included within the analyses controlling for all other variables included in the model or controlled for within the analytic framework. An odds ratio above one is interpreted as an increase in the likelihood of an event occurring. Thus middleborns were found to be 33 percent more likely than firstborns to engage in problem behavior net of controls and lastborns were 20 percent more likely than firstborns to engage in problem behavior net of controls. Model 2 provides the results of the mediation analysis. The mediating variables 7 were not able to account for much of the observed differences between firstborns and middleborns or firstborns and lastborns; however, a reduction in the magnitude of each difference was observed (reductions of 11 percent and 33 percent respectively), though the effects of birth order remained statistically significant. Intact family, race dummy variables (black), GPA, parental presence, and parental closeness were found to significantly decrease the likelihood of problem behavior, while family income, age, gender (male), and PVT were found to significantly increase the likelihood of problem behavior.

Examining the Effects of Birth Order on Delinquency: Within-Family Analyses

Despite the findings shown above of significant relationships between birth order and delinquency, the question remains whether these associations are indeed causal or spurious (or artifacts of the between-individual analyses). To address these concerns, Table 3 provides the results of the logistic regression fixed effects model examining within-family effects of birth order on problem behavior. Model 1 indicates that within families, engagement in problem behavior is not significantly affected by birth order. Both of the previously significant effects of middleborns and lastborns were found to be non-significant. Moreover, the effect size of middleborns was reduced by 50 percent (non-significant odds ratio of 1.14) and the effect of lastborns changed directions. Only the effect of gender remained a statistically significant predictor of engagement in problem behavior. In Model 2 the potential mediators are added to the model. Only the measure of GPA and parental closeness were found to be statistically significant, with both predicting a lower likelihood of engagement in problem behavior. Important to note in the logistic regression fixed effect model is the absence of any variable that would be stable across all members of the sibship, as these measures are controlled for within the analytic framework. This means variables such as family income, family education, intact family, and sibship size are excluded from the analytic model, but their effects are controlled for within the fixed effects methodology. Additionally, it is important to note that other variables that would be stable across all members of the sibship that were not measured including location of home, parental discipline style, and unmeasured family resources are also controlled for in the fixed effects methodology.

Note: 1,121 Families or 2,294 Adolescents were dropped from the analyses due to lack of variation among siblings

In summary, significant effects for birth order on delinquency exist when controlling for individual and family characteristics at the between-individual level. However, when analyzing the effects of birth order at the within-family level the effects of birth order on delinquency become non-significant.

Research concerning the effects of birth order has a long and storied past, complete with peaks of popularity (1950's, 1960's, and 1990's) and valleys of disfavor (1970's and 1980's). A relatively recent re-imagination of birth order theory by Sulloway (1996) has served to reignite debate surrounding the true effects of birth order. Given this rebirth of interest into the effects of birth order (especially concerning intelligence), criticisms have re-emerged questioning previous studies' use of between-individual designs ( Retherford & Sewell, 1991 ; Rodgers, 2001 ; Rodgers et al., 2000 ; Wichman, 2006 ). Adler's birth order theory and Sulloway's born to rebel hypothesis both hypothesize that the effects of birth order lie within-families; yet, the majority of studies designed to test this very hypothesis rely on a between-individual comparisons. This research sought to build upon this body of work, especially the research of Rahav (1980) and Argys et al. (2006) , in determining the effects of birth order upon delinquency utilizing both between-individual and within-family designs.

The results from the between-individual analyses of problem behavior provide support for both Hypothesis 1 and Hypothesis 2 . While both hypotheses are supported, Hypothesis 2 derived from Sulloway's born to rebel hypothesis was found to have greater support as curvilinearity in the effect of birth order was not observed. While firstborns were significantly less likely to engage in problem behavior than middleborn or lastborns, lastborns did not significantly differ in their likelihood of engagement in problem behavior from middleborns. The lack of a significant difference between middleborns and lastborns thus provides greater support for Sulloway's conceptualization of birth order as a dichotomy (firstborns and lastborns). Additionally, the significant effects observed for birth order were observed even in the most conservative statistical model (i.e. the mediation model).

Nonetheless, given the recent criticisms regarding between-individual study designs, I utilized a fixed effects methodology and re-analyzed the statistically significant outcomes. The results of the within-family analyses provide strong and consistent support for the null hypothesis. The significant outcomes observed in the between-individual analyses, were found to be non-significant when examined under a within families design. It is important to note that due to data restrictions, the within-family models utilize a smaller sample than the between-individual models. While the sample size is significantly lower, power analyses using Stata's POWERLOG command indicate that to observe the effects observed in the between-individual study design approximately 450 observations are needed. The within-family sample contains over 3,800 observations and the analysis included approximately 1,500 observations and 655 family groups. In light of the power analysis the within-family sample contains more than enough observations and family groups necessary to detect the same effect observed in the between-individual analysis. Given the lack of significance within-families, the effects of birth order observed between-individuals seem to indicate that some unobserved family characteristic is driving the relationship between birth order and delinquency. This finding adds to a growing literature criticizing the continued study of birth order without adequately considering possible unobserved or spurious influences.

This research improves upon previous research with its use of sophisticated statistical procedures, a large nationally representative sample, and examination of both between-individuals and within-family differences. The combination of the methods and data yield more reliable and convincing results, especially when compared to previous analyses that have had difficulty in controlling for potentially confounding variables and selection effects. Along with its advancements, this research also has some limitations. First, the explanatory variables utilized might not reflect difficult to measure concepts such as rebellion. Though I use a variety of components in my problem behavior composite, I still might not be able to capture the “rebelliousness” (or openness to radical change) that Sulloway found in his historical analysis. Recall that Sulloway's original conception of rebellion was a historical analysis of participants in scientific controversies. Sulloway's original measurement of “rebellion” attempted to utilize Eysenck's conservatism-radicalism scale. A fair criticism of Sulloway's hypothesis is that what he is calling rebellion may be overstated. Individuals were considered to be rebellious if they went against or attempted to upset the status quo. Eysenck's conservatism-radicalism scale specifically taps into attitudes about punishment, government, and war. While my outcome measure differs from that of Sulloway's, I argue that they are in line with Sulloway's basic premise that laterborns strive to upset the status quo to enable more equal competition. In the case of the problem behaviors discussed in the paper, then, laterborns should be more likely than firstborns to engage in these behaviors in an effort to gain a greater share of parental resources (i.e. parental time and attention).

Second, the within-family analyses utilize a far smaller sample than the between-individual analyses. The use of the smaller sample could potentially be underestimating the significance of the effects of birth order. Nonetheless, as I have noted above, results of power analyses indicate that my within-families sample has more than enough observations to reliably detect the same effect observed in the between-individual analyses. In addition to potentially underestimating the significance of effects of birth order there is also potential for selection bias in the within-family sample. I test for the potential effect of selection by presenting and comparing descriptive statistics for both the between-individual and within-family samples. Comparisons of the descriptive statistics reveal no significant differences in the variables used in analyses between the two analytic samples.

Finally, while my findings suggest an unobserved family factor driving the relationship between birth order and delinquency, the analyses do not necessarily provide a clear picture of what the unobserved factor could be. Based upon prior research examining the link between families and crime, as well as siblings and crime, I can only speculate as to the possible unobserved factors. First, while my analyses include measures of parental closeness and parental monitoring, my analyses do not control for the quality of parenting that can fluctuate from family to family. Research by Larzelere and Patterson (1990) provided evidence that family management practices (specifically discipline and supervision) are strong predictors of delinquency. The impact of parental discipline in the relationship between birth order and delinquency would in theory restrict juveniles' opportunity structures to commit delinquent acts as well as serve as a deterrent to repeated offenses. Second, based upon research by Haynie (2001 , 2002 ) and Haynie and Osgood (2005) , the significant differences observed in the between-individual analyses may be a product of delinquent peers or delinquent peer networks. My analyses are focused specifically on variables related to families, thus neglecting other potentially influential factors such as peers. Finally, research by Widmer (1997) , Conger (1999) , Slomkowski et al. (2001) , and Conger et al. (2003) suggests that older siblings are influential in shaping the behaviors and norms adopted by younger siblings. Therefore, adolescents with older siblings who exhibit deviant behavior will be more likely to mimic this behavior at an earlier age. Given differences in sibling spacing or density, one could explain the between-individual results as an example of younger siblings mimicking the behavior of older siblings not included in this study. However, in the within-family analyses cases in which there existed no variation among siblings in the problem behavior composite (either all delinquent or all non-delinquent) were excluded. The number of exclusion sibships excluded from the analyses due to non-variation on the outcome measure may provide some evidence of the influence of older siblings on younger siblings.

In conclusion, the results of these analyses suggest that birth order provides a rather negligible role in shaping adolescents' delinquent behavior when the analyses take into account within-family characteristics. As demonstrated in this research, birth order research which continues to utilize a between-individuals design is capable of observing significant effects in even the most conservative of statistical models; however, when the more appropriate within-family design is utilized the effects become non-significant suggesting that the observed effects are the product of some family-level characteristic not captured in the between-individuals analyses. While birth order theories, as evidenced by the results, are not necessary in delinquency research, the analyses point to other family mechanisms (intact family, family education, parental supervision, and parental closeness) that offer consistent predictions in regards to delinquent outcomes. Examination of the direct effect of birth order may be misplacing the focus of what matters more, i.e. family-level social processes. While direct effects were not observed it may be in haste to neglect the study of the indirect effects of birth order that may condition reporting of certain family mechanisms (parental closeness, and parental supervision). Further research is necessary to test for the effects of the family mechanisms discussed above, as well as analyze the influence of the sibling relationship in regards to delinquent or problem behavior outcomes.

Appendix: Problem Behavior Composite Measure Components

1 In an effort to avoid confusion in reading the term “single child” will be used when discussing children with no siblings, otherwise known as only children.

2 Laterborns is a term used to describe children in the family that were not firstborn.

3 Sibship is a term that refers to all siblings within one family.

4 This paper focuses on examining the link between biological birth order and delinquency. Thus, personality profiles of step children and adopted children will not be discussed at length. However, it is theorized ( Toman 1993 ) that step children will typically keep the role they filled in their biological family with the possibility of playing multiple roles; adopted children will typically accept the role associated with their ordinal position in terms of the rest of the siblings, most problems in role assumption arise if the adopted child has already had significant socialization.

5 Twins are not mentioned at exceptional length within this study as it has been theorized (Wilson 1981, Toman 1993 ) that twins will typically adopt the same birth order role aside from the role of an only child; thus the possibility exists that you may have multiple firstborns, middleborns, and youngest children.

6 I am limited by the data in my ability to assess the age gaps from sibling to sibling if not all siblings were sampled. Given the exclusion of adolescents who were adopted, the likely limited effect of mortality in my sample, and my control for intact family, I feel that the effect of differences between biological and functional birth order would be quite limited and would not substantively alter my findings.

7 In analyses not presented birth order variables were shown to be significantly related to each of the potentially mediating variables. Where both middleborns and laterborns were found to lower levels of each of the mediating variables (i.e. parental presence, parental closeness, GPA, and PVT score).

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